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What are the key benefits of using AI in software testing

What are the key benefits of using AI in software testing

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What are the key benefits of using AI in software testing

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  1. What are the key benefits of using AI in software testing? The platform of Artificial Intelligence (AI) is already making waves in the software development industry by proving to be a huge benefactor. Upon that, AI is steadily creating a strategic need in the domain of software testing and for profitable and productive reasons. In fact, AI in testing is actually proving to be a strategic and rewarding move as the testing activities are carried out in a more efficient and rapid manner. In this article, you will get to know the key benefits of using AI in software testing. Following are the key benefits of implementing Artificial Intelligence (AI) in software testing: 02 01 03 Visual testing can be tactically performed Faster time-to-market Enhanced accuracy The significance of automated API test generation Regression tests are enhanced 06 05 Overall test coverage is maximized 04 Improved efficiency and clarity in writing test cases 07 1. Enhanced accuracy: Manual testing will be beset with errors, as manual testers are involved to carry on with the testing process. With the inclusion of AI automation testing, the testing process can be carried out rapidly and with great accuracy, thereby providing optimal testing outcomes. Testers can focus on other complex features of the application. AI can perform testing activities exactly as per the plan, thereby being able to complete recurring tasks effectively and continually. 2. Faster time-to-market: Whenever source code is customized, software testing is performed. To carry out manual testing can prove to be a time-consuming process. With the implementation of AI automated tests, the costs are low and the testing activity is carried out rapidly. The entire software testing process can be reduced from days to mere hours, which, in turn, translates to lower costs. 3. Visual testing can be tactically performed: AI uses image recognition and pattern recognition, so that visual bugs can be discovered by performing visual testing of apps, and making sure that all the visual elements function and look accordingly. Dynamic UI controls can be distinguished through the AI platform, despite their size and shape, thus evaluating them on a pixel level. 4. Overall test coverage is maximized: The overall scope and depth of tests can be enhanced by AI automated testing. AI testing can assess the memory and file states, program states and data tables to know whether the software product is working as per the required expectations. Around 1000+ test cases can be performed by automation, which means huge test coverage can be easily expected. The tests don’t fail, regardless of whether a property of a component changes. 5. Regression tests are enhanced: Regression tests are required with progressive and rapid deployment. Tedious regression tests can be effectively performed by AI. Machine learning can be adopted by organizations to create test scripts. For example, to scan for any overlaps, when a change is made in the User interface, the AI testing platform can be effectively used. The alterations can also be validated by the AI testing platform. 6. The significance of automated API test generation: Multiple test cases can be developed by users using API testing automation for API quality assurance and also deciding upon the requirement of numerous third-party tools. Large volumes of data are easily analyzed by AI-based tools and then assess quickly, whether the API is functioning correctly or not. 7. Improved efficiency and clarity in writing test cases: The test case quality for automation testing can be improved by the AI platform. Real test cases will be offered by the AI platform that is easy to regulate and quick to operate. Additional possibilities for test cases cannot be properly analyzed by developers using the traditional method. Project data analysis can happen in a matter of just a few minutes or seconds through the use of an AI platform. New approaches to test cases can be figured out by the developers. CONCLUSION If you are looking forward to implementing AI testing for your specific project, then do get connected with a premium software testing Services Company that will provide you with a tactical testing roadmap that is in line with your project specific requirements. www.TestingXperts.com To know more about our services please email us at info@testingxperts.com USA | CANADA | UK | NETHERLANDS | SOUTH AFRICA | INDIA | SINGAPORE © 2022 TestingXperts, All Rights Reserved © www.testingxperts.com

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